东南大学学报（英文版）2003，Vol.19Issue(4)：307-310,4.
基于支持向量机的语音情感识别
Support vector machines for emotion recognition in Chinese speech
摘要
Abstract
Support vector machines (SVMs) are utilized for emotion recognition in Chinese speech in this paper. Both binary-class discrimination and the multi-class discrimination are discussed. It proves that the emotional features construct a nonlinear problem in the input space, and SVMs based on nonlinear mapping can solve it more effectively than other linear methods. Multi-class classification based on SVMs with a soft decision function is constructed to classify the four emotion situations. Compared with principal component analysis (PCA) method and modified PCA method, SVMs perform the best result in multi-class discrimination by using nonlinear kernel mapping.关键词
语音信号/情感识别/支持向量机Key words
speech signal/emotion recognition/support vector machines分类
信息技术与安全科学引用本文复制引用
王治平,赵力,邹采荣..基于支持向量机的语音情感识别[J].东南大学学报（英文版）,2003,19(4):307-310,4.基金项目
Education Revitalization Program Oriented to the 21st Century under the Chinese Ministry of Education. （）
